The Impacts of Battery Electric Vehicles on the Power Grid: A Monte Carlo Method Approach

Teresa Nogueira, José Magano, Ezequiel Sousa and Gustavo R. Alves
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Teresa Nogueira: School of Engineering, Polytechnic Institute of Porto, P. Porto, 4249-015 Porto, Portugal
José Magano: Research Center in Business and Economics (CICEE), Universidade Autónoma de Lisboa, 1150-293 Lisboa, Portugal
Ezequiel Sousa: School of Engineering, Polytechnic Institute of Porto, P. Porto, 4249-015 Porto, Portugal
Gustavo R. Alves: School of Engineering, Polytechnic Institute of Porto, P. Porto, 4249-015 Porto, Portugal

Energies, 2021, vol. 14, issue 23, 1-18

Abstract: Balancing energy demand and supply will become an even greater challenge considering the ongoing transition from traditional fuel to electric vehicles (EV). The management of this task will heavily depend on the pace of the adoption of light-duty EVs. Electric vehicles have seen their market share increase worldwide; the same is happening in Portugal, partly because the government has kept incentives for consumers to purchase EVs, despite the COVID-19 pandemic. The consequent shift to EVs entails various challenges for the distribution network, including coping with the expected growing demand for power. This article addresses this concern by presenting a case study of an area comprising 20 municipalities in Northern Portugal, for which battery electric vehicles (BEV) sales and their impact on distribution networks are estimated within the 2030 horizon. The power required from the grid is estimated under three BEV sales growth deterministic scenarios based on a daily consumption rate resulting from the combination of long- and short-distance routes. A Monte Carlo computational simulation is run to account for uncertainty under severe EV sales growth. The analysis is carried out considering three popular BEV models in Portugal, namely the Nissan Leaf, Tesla Model 3, and Renault Zoe. Their impacts on the available power of the distribution network are calculated for peak and off-peak hours. The results suggest that the current power grid capacity will not cope with demand increases as early as 2026. The modeling approach could be replicated in other regions with adjusted parameters.

Keywords: BEV; PHEV; electric vehicles; EV sales; energy demand; distribution grid; power impact (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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